Spatial and temporal patterns of territory use of male California sea lions (Zalophus californianus) in the Gulf of California, Mexico
Bibliographic record
Abstract
Little is known about the spatial distribution patterns of territory use throughout the breeding season and the potential influence of these patterns on male behavior and fitness for California sea lions ( Zalophus californianus (Lesson, 1828)). We used empirical data from behavioral observations to document the distribution of 1271 territories during the 2004–2006 breeding seasons at three breeding colonies in the Gulf of California, Mexico. Territories were depicted as circular objects and overlaid over one another in ArcINFO®, separated by island and year. Areas with consistent overlap in territory use were identified among years. Territory boundaries and locations were spatially distinct within breeding seasons and at each of the breeding colonies. Males occurring in these areas were partially influenced by island, year, territory size, number of females, aggressive interactions, and distance to nearest neighbor (best fitting model — AIC = 1273.09, ωi= 0.99). However, the best model only accounted for 30% of the variation, indicating that other variables are needed to explain the occurrence of these “hot spots”. Territory site selection, therefore, may be influenced by extrinsic factors under which female choice may be operating resembling a lek-like mating system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".